Eugene Vorontsov
Eugene Vorontsov
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The importance of skip connections in biomedical image segmentation
M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal
International Workshop on Deep Learning in Medical Image Analysis …, 2016
Deep Learning: A Primer for Radiologists
G Chartrand, PM Cheng, E Vorontsov, M Drozdzal, S Turcotte, CJ Pal, ...
RadioGraphics 37 (7), 2113-2131, 2017
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B van Ginneken, ...
arXiv preprint arXiv:1902.09063, 2019
The medical segmentation decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ...
Nature Communications 13 (1), 1-13, 2022
Learning normalized inputs for iterative estimation in medical image segmentation
M Drozdzal, G Chartrand, E Vorontsov, M Shakeri, L Di Jorio, A Tang, ...
Medical Image Analysis, 2017
On orthogonality and learning recurrent networks with long term dependencies
E Vorontsov, C Trabelsi, S Kadoury, C Pal
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Liver lesion segmentation informed by joint liver segmentation
E Vorontsov, A Tang, C Pal, S Kadoury
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
Deep learning and data labeling for medical applications
M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal
LNCS 10008, 179-187, 2016
Deep learning for automated segmentation of liver lesions at CT in patients with colorectal cancer liver metastases
E Vorontsov, M Cerny, P Régnier, L Di Jorio, CJ Pal, R Lapointe, ...
Radiology: Artificial Intelligence 1 (2), 180014, 2019
Towards non-saturating recurrent units for modelling long-term dependencies
S Chandar, C Sankar, E Vorontsov, SE Kahou, Y Bengio
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3280-3287, 2019
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
G Kerg, K Goyette, MP Touzel, G Gidel, E Vorontsov, Y Bengio, G Lajoie
Advances in Neural Information Processing Systems, 13613-13623, 2019
Dynamics and Distribution of Klothoβ (KLB) and Fibroblast Growth Factor Receptor-1 (FGFR1) in Living Cells Reveal the Fibroblast Growth Factor-21 (FGF21)-induced Receptor Complex
AYK Ming, E Yoo, EN Vorontsov, SM Altamentova, DM Kilkenny, ...
Journal of Biological Chemistry 287 (24), 19997-20006, 2012
Metastatic liver tumor segmentation using texture-based omni-directional deformable surface models
E Vorontsov, N Abi-Jaoudeh, S Kadoury
Abdominal Imaging. Computational and Clinical Applications: 6th …, 2014
Metastatic liver tumour segmentation from discriminant Grassmannian manifolds
S Kadoury, E Vorontsov, A Tang
Physics in Medicine & Biology 60 (16), 6459, 2015
Towards semi-supervised segmentation via image-to-image translation
E Vorontsov, P Molchanov, C Beckham, W Byeon, S De Mello, V Jampani, ...
arXiv preprint arXiv:1904.01636, 2019
Metastatic liver tumour segmentation with a neural network-guided 3D deformable model
E Vorontsov, A Tang, D Roy, CJ Pal, S Kadoury
Medical & biological engineering & computing, 1-13, 2016
Virchow: A million-slide digital pathology foundation model
E Vorontsov, A Bozkurt, A Casson, G Shaikovski, M Zelechowski, S Liu, ...
arXiv preprint arXiv:2309.07778, 2023
Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks
WT Le, E Vorontsov, FP Romero, L Seddik, MM Elsharief, PF Nguyen-Tan, ...
Scientific Reports 12 (1), 3183, 2022
Label noise in segmentation networks: mitigation must deal with bias
E Vorontsov, S Kadoury
Deep Generative Models, and Data Augmentation, Labelling, and Imperfections …, 2021
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